Protocol matters: which methylome are you actually studying?

Profiling DNA methylation differences between inbred mouse strains on the Illumina Human Infinium MethylationEPIC microarray

The Illumina Infinium MethylationEPIC provides an efficient platform for profiling DNA methylation in humans at over 850,000 CpGs. Model organisms such as mice do not currently benefit from an equivalent array. Here we used this array to measure DNA methylation in mice. We defined probes targeting conserved regions and performed differential methylation analysis and compared between the array-based assay and affinity-based DNA sequencing of methyl-CpGs (MBD-seq) and reduced representation bisulfite sequencing. Mouse samples consisted of 11 liver DNA from two strains, C57BL/6J (B6) and DBA/2J (D2), that varied widely in age. Linear regression was applied to detect differential methylation. In total, 13,665 probes (1.6% of total probes) aligned to conserved CpGs. Beta-values (β-value) for these probes showed a distribution similar to that in humans. Overall, there was high concordance in methylation signal between the EPIC array and MBD-seq (Pearson correlation r = 0.70, p-value < 0.0001). However, the EPIC probes had higher quantitative sensitivity at CpGs that are hypo- (β-value < 0.3) or hypermethylated (β-value > 0.7). In terms of differential methylation, no EPIC probe detected a significant difference between age groups at a Benjamini-Hochberg threshold of 10%, and the MBD-seq performed better at detecting age-dependent change in methylation. However, the top most significant probe for age (cg13269407; uncorrected p-value = 1.8 x 10-5) is part of the clock CpGs used to estimate the human epigenetic age. For strain, 219 EPIC probes detected significant differential methylation (FDR cutoff 10%) with ~80% CpGs associated with higher methylation in D2. This higher methylation profile in D2 compared to B6 was also replicated by the MBD-seq data. To summarize, we found only a small subset of EPIC probes that target conserved sites. However, for this small subset the array provides a reliable assay of DNA methylation and can be effectively used to measure differential methylation in mice.

Efficiency of methylated DNA immunoprecipitation bisulphite sequencing for whole-genome DNA methylation analysis

AIMS

We compared four common methods for measuring DNA methylation levels and recommended the most efficient method in terms of cost and coverage.

MATERIALS & METHODS

The DNA methylation status of liver and stomach tissues was profiled using four different methods, whole-genome bisulphite sequencing (WG-BS), targeted bisulphite sequencing (Targeted-BS), methylated DNA immunoprecipitation sequencing (MeDIP-seq) and methylated DNA immunoprecipitation bisulphite sequencing (MeDIP-BS). We calculated DNA methylation levels using each method and compared the results.

RESULTS

MeDIP-BS yielded the most similar DNA methylation profile to WG-BS, with 20 times less data, suggesting remarkable cost savings and coverage efficiency compared with the other methods.

CONCLUSION

MeDIP-BS is a practical cost-effective method for analyzing whole-genome DNA methylation that is highly accurate at base-pair resolution.

Single-CpG resolution mapping of 5-hydroxymethylcytosine by chemical labeling and exonuclease digestion identifies evolutionarily unconserved CpGs as TET targets

Conventional techniques for single-base resolution mapping of epigenetic modifications of DNA such as 5-hydroxymethylcytosine (5hmC) rely on the sequencing of bisulfite-modified DNA. Here we present an alternative approach called SCL-exo which combines selective chemical labeling (SCL) of 5hmC in genomic DNA with exonuclease (exo) digestion of the bead-trapped modified DNA molecules. Associated with a straightforward bioinformatic analysis, this new procedure provides an unbiased and fast method for mapping this epigenetic mark at high resolution. Implemented on mouse genomic DNA from in vitro-differentiated neural precursor cells, SCL-exo sheds light on an intrinsic lack of conservation of hydroxymethylated CpGs across vertebrates.

Coordinated epigenetic remodelling of transcriptional networks occurs during early breast carcinogenesis

Background

Dysregulation of the epigenome is a common event in malignancy; however, deciphering the earliest cancer-associated epigenetic events remains a challenge. Cancer epigenome studies to date have primarily utilised cancer cell lines or clinical samples, where it is difficult to identify the initial epigenetic lesions from those that occur over time. Here, we analysed the epigenome of human mammary epithelial cells (HMEC) and a matched variant cell population (vHMEC) that have spontaneously escaped senescence and undergone partial carcinogenic transformation. Using this model of basal-like breast carcinogenesis, we provide striking new insights into the very first epigenetic changes that occur during the initial stages of malignancy.

Results

The first phase of malignancy is defined by coordinated changes in the epigenome. At the chromatin level, this is embodied in long-range epigenetic deregulation, which involves the concomitant but atypical acquisition or loss of active and repressive histone modifications across large regional blocks. Changes in DNA methylation also occurs in a highly coordinated manner. We identified differentially methylated regions (DMRs) in the very earliest passages of vHMECs. Notably, we find that differential methylation targets loci regulated by key transcription factors including p53, AHR and E2F family members suggesting that epigenetic deregulation of transcription factor binding is a key event in breast carcinogenesis. Interestingly, DMRs identified in vHMEC are extensively methylated in breast cancer, with hypermethylation frequently encroaching into neighbouring regions. A subset of vHMEC DMRs exhibited a strong basal-like cancer specific hypermethylation.

Conclusions

Here, we generated epigenome-wide maps of the earliest phase of breast malignancy and show long-range epigenetic deregulation and coordinated DNA hypermethylation targets loci regulated by key transcription factors. These findings support a model where induction of breast cancer occurs through epigenetic disruption of transcription factor binding leading to deregulation of cancer-associated transcriptional networks. With their stability and very early occurrence, vHMECs hypermethylated loci could serve as excellent biomarkers for the initial detection of basal breast cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-015-0086-0) contains supplementary material, which is available to authorized users.

Ancestry dependent DNA methylation and influence of maternal nutrition

There is extensive variation in DNA methylation between individuals and ethnic groups. These differences arise from a combination of genetic and non-genetic influences and potential modifiers include nutritional cues, early life experience, and social and physical environments. Here we compare genome-wide DNA methylation in neonatal cord blood from African American (AA; N = 112) and European American (EA; N = 91) participants of the CANDLE Study (Conditions Affecting Neurocognitive Development and Learning in Early Childhood). Our goal is to determine if there are replicable ancestry-specific methylation patterns that may implicate risk factors for diseases that have differential prevalence between populations. To identify the most robust ancestry-specific CpG sites, we replicate our results in lymphoblastoid cell lines from Yoruba African and CEPH European panels of HapMap. We also evaluate the influence of maternal nutrition--specifically, plasma levels of vitamin D and folate during pregnancy--on methylation in newborns. We define stable ancestry-dependent methylation of genes that include tumor suppressors and cell cycle regulators (e.g., APC, BRCA1, MCC). Overall, there is lower global methylation in African ancestral groups. Plasma levels of 25-hydroxy vitamin D are also considerably lower among AA mothers and about 60% of AA and 40% of EA mothers have concentrations below 20 ng/ml. Using a weighted correlation analysis, we define a network of CpG sites that is jointly modulated by ancestry and maternal vitamin D. Our results show that differences in DNA methylation patterns are remarkably stable and maternal micronutrients can exert an influence on the child epigenome.

Genome-wide assays that identify and quantify modified cytosines in human disease studies

The number of different assays that has been published to study DNA methylation is extensive, complemented by recently described assays that test modifications of cytosine other than the most abundant 5-methylcytosine (5mC) variant. In this review, we describe the considerations involved in choosing how to study 5mC throughout the genome, with an emphasis on the common application of testing for epigenetic dysregulation in human disease. While microarray studies of 5mC continue to be commonly used, these lack the additional qualitative information from sequencing-based approaches that is increasingly recognized to be valuable. When we test the representation of functional elements in the human genome by several current assay types, we find that no survey approach interrogates anything more than a small minority of the nonpromoter cis-regulatory sites where DNA methylation variability is now appreciated to influence gene expression and to be associated with human disease. However, whole-genome bisulphite sequencing (WGBS) adds a substantial representation of loci at which DNA methylation changes are unlikely to be occurring with transcriptional consequences. Our assessment is that the most effective approach to DNA methylation studies in human diseases is to use targeted bisulphite sequencing of the cis-regulatory loci in a cell type of interest, using a capture-based or comparable system, and that no single design of a survey approach will be suitable for all cell types.

An integrated epigenomic analysis for type 2 diabetes susceptibility loci in monozygotic twins

DNA methylation has a great potential for understanding the aetiology of common complex traits such as Type 2 diabetes (T2D). Here we perform genome-wide methylated DNA immunoprecipitation sequencing (MeDIP-seq) in whole-blood-derived DNA from 27 monozygotic twin pairs and follow up results with replication and integrated omics analyses. We identify predominately hypermethylated T2D-related differentially methylated regions (DMRs) and replicate the top signals in 42 unrelated T2D cases and 221 controls. The strongest signal is in the promoter of the MALT1 gene, involved in insulin and glycaemic pathways, and related to taurocholate levels in blood. Integrating the DNA methylome findings with T2D GWAS meta-analysis results reveals a strong enrichment for DMRs in T2D-susceptibility loci. We also detect signals specific to T2D-discordant twins in the GPR61 and PRKCB genes. These replicated T2D associations reflect both likely causal and consequential pathways of the disease. The analysis indicates how an integrated genomics and epigenomics approach, utilizing an MZ twin design, can provide pathogenic insights as well as potential drug targets and biomarkers for T2D and other complex traits.

Type 2 diabetes (T2D) is a highly heterogeneous disease with a strong genetic component. Here the authors examine genome-wide methylation patterns in T2D-discordant, T2D-concordant and healthy concordant monozygotic twin pairs, and identify DNA methylation signals that may represent new biomarkers or drug targets for T2D.

Statistical methods for detecting differentially methylated loci and regions

DNA methylation, the reversible addition of methyl groups at CpG dinucleotides, represents an important regulatory layer associated with gene expression. Changed methylation status has been noted across diverse pathological states, including cancer. The rapid development and uptake of microarrays and large scale DNA sequencing has prompted an explosion of data analytic methods for processing and discovering changes in DNA methylation across varied data types. In this mini-review, we present a compact and accessible discussion of many of the salient challenges, such as experimental design, statistical methods for differential methylation detection, critical considerations such as cell type composition and the potential confounding that can arise from batch effects. From a statistical perspective, our main interests include the use of empirical Bayes or hierarchical models, which have proved immensely powerful in genomics, and the procedures by which false discovery control is achieved.

Recurrent epimutations activate gene body promoters in primary glioblastoma

Aberrant DNA hypomethylation may play an important role in the growth rate of glioblastoma (GBM), but the functional impact on transcription remains poorly understood. We assayed the GBM methylome with MeDIP-seq and MRE-seq, adjusting for copy number differences, in a small set of non-glioma CpG island methylator phenotype (non-G-CIMP) primary tumors. Recurrent hypomethylated loci were enriched within a region of chromosome 5p15 that is specified as a cancer amplicon and also encompasses TERT, encoding telomerase reverse transcriptase, which plays a critical role in tumorigenesis. Overall, 76 gene body promoters were recurrently hypomethylated, including TERT and the oncogenes GLI3 and TP73. Recurring hypomethylation also affected previously unannotated alternative promoters, and luciferase reporter assays for three of four of these promoters confirmed strong promoter activity in GBM cells. Histone H3 lysine 4 trimethylation (H3K4me3) ChIP-seq on tissue from the GBMs uncovered peaks that coincide precisely with tumor-specific decrease of DNA methylation at 200 loci, 133 of which are in gene bodies. Detailed investigation of TP73 and TERT gene body hypomethylation demonstrated increased expression of corresponding alternate transcripts, which in TP73 encodes a truncated p73 protein with oncogenic function and in TERT encodes a putative reverse transcriptase-null protein. Our findings suggest that recurring gene body promoter hypomethylation events, along with histone H3K4 trimethylation, alter the transcriptional landscape of GBM through the activation of a limited number of normally silenced promoters within gene bodies, in at least one case leading to expression of an oncogenic protein.

BayMeth: improved DNA methylation quantification for affinity capture sequencing data using a flexible Bayesian approach

Affinity capture of DNA methylation combined with high-throughput sequencing strikes a good balance between the high cost of whole genome bisulfite sequencing and the low coverage of methylation arrays. We present BayMeth, an empirical Bayes approach that uses a fully methylated control sample to transform observed read counts into regional methylation levels. In our model, inefficient capture can readily be distinguished from low methylation levels. BayMeth improves on existing methods, allows explicit modeling of copy number variation, and offers computationally efficient analytical mean and variance estimators. BayMeth is available in the Repitools Bioconductor package.

Analysis of epigenetic modifications of DNA in human cells

Epigenetics, the study of somatically heritable changes in gene expression not related to changes in the DNA sequence, is a rapidly expanding research field that plays important roles in healthy as well as in diseased cells. DNA methylation and hydroxymethylation are epigenetic modifications found in human cells, which are deeply implicated in normal cellular processes as well as in several major human diseases. Here, a range of different methods for the analyses of DNA methylation and hydroxymethylation at locus-specific and genome-wide scales is described.

Functional DNA methylation differences between tissues, cell types, and across individuals discovered using the M&M algorithm

DNA methylation plays key roles in diverse biological processes such as X chromosome inactivation, transposable element repression, genomic imprinting, and tissue-specific gene expression. Sequencing-based DNA methylation profiling provides an unprecedented opportunity to map and compare complete DNA methylomes. This includes one of the most widely applied technologies for measuring DNA methylation: methylated DNA immunoprecipitation followed by sequencing (MeDIP-seq), coupled with a complementary method, methylation-sensitive restriction enzyme sequencing (MRE-seq). A computational approach that integrates data from these two different but complementary assays and predicts methylation differences between samples has been unavailable. Here, we present a novel integrative statistical framework M&M (for integration of MeDIP-seq and MRE-seq) that dynamically scales, normalizes, and combines MeDIP-seq and MRE-seq data to detect differentially methylated regions. Using sample-matched whole-genome bisulfite sequencing (WGBS) as a gold standard, we demonstrate superior accuracy and reproducibility of M&M compared to existing analytical methods for MeDIP-seq data alone. M&M leverages the complementary nature of MeDIP-seq and MRE-seq data to allow rapid comparative analysis between whole methylomes at a fraction of the cost of WGBS. Comprehensive analysis of nineteen human DNA methylomes with M&M reveals distinct DNA methylation patterns among different tissue types, cell types, and individuals, potentially underscoring divergent epigenetic regulation at different scales of phenotypic diversity. We find that differential DNA methylation at enhancer elements, with concurrent changes in histone modifications and transcription factor binding, is common at the cell, tissue, and individual levels, whereas promoter methylation is more prominent in reinforcing fundamental tissue identities.

Methods for cancer epigenome analysis

Accurate detection of epimutations in tumor cells is crucial for -understanding the molecular pathogenesis of cancer. Alterations in DNA methylation in cancer are functionally important and clinically relevant, but even this well-studied area is continually re-evaluated in light of unanticipated results, such as the strong association between aberrant DNA methylation in adult tumors and polycomb group profiles in embryonic stem cells, cancer-associated genetic mutations in epigenetic regulators such as DNMT3A and TET family genes, and the discovery of altered 5-hydroxymethylcytosine, a product of TET proteins acting on 5-methylcytosine, in human tumors with TET mutations. The abundance and distribution of covalent histone modifications in primary cancer tissues relative to normal cells is an important but largely uncharted area, although there is good evidence for a mechanistic role of cancer-specific alterations in histone modifications in tumor etiology, drug response, and tumor progression. Meanwhile, the discovery of new epigenetic marks continues, and there are many useful methods for epigenome analysis applicable to primary tumor samples, in addition to cancer cell lines. For DNA methylation and hydroxymethylation, next-generation sequencing allows increasingly inexpensive and quantitative whole-genome profiling. Similarly, the refinement and maturation of chromatin immunoprecipitation with next-generation sequencing (ChIP-seq) has made possible genome-wide mapping of histone modifications, open chromatin, and transcription factor binding sites. Computational tools have been developed apace with these epigenome methods to better enable accurate interpretation of the profiling data.

Single-molecule, genome-scale analyses of DNA modifications: exposing the epigenome with next-generation technologies

DNA modifications represent an integral part of the epigenome and they have a pivotal role in regulation of genome function. Despite the wide variety of analytical techniques that have been developed to detect DNA modifications, their investigation at the single-genome level is only beginning to emerge. In contrast to population-averaged analyses, single-molecule approaches potentially allow the mapping of epigenetic linkage between distantly located genomic regions, the locus-specific analysis of repetitive DNA elements, as well as determination of allele-specific DNA modification patterns. In this article, the properties of current single-molecule analyses of DNA modifications will be discussed and compared. In addition, the possible biomedical and discovery research applications of single-molecule epigenomics will be highlighted.

Copy-number-aware differential analysis of quantitative DNA sequencing data

Developments in microarray and high-throughput sequencing (HTS) technologies have resulted in a rapid expansion of research into epigenomic changes that occur in normal development and in the progression of disease, such as cancer. Not surprisingly, copy number variation (CNV) has a direct effect on HTS read densities and can therefore bias differential detection results. We have developed a flexible approach called ABCD-DNA (affinity-based copy-number-aware differential quantitative DNA sequencing analyses) that integrates CNV and other systematic factors directly into the differential enrichment engine.

A comparison of the whole genome approach of MeDIP-seq to the targeted approach of the Infinium HumanMethylation450 BeadChip(®) for methylome profiling

DNA methylation is one of the most studied epigenetic marks in the human genome, with the result that the desire to map the human methylome has driven the development of several methods to map DNA methylation on a genomic scale. Our study presents the first comparison of two of these techniques - the targeted approach of the Infinium HumanMethylation450 BeadChip® with the immunoprecipitation and sequencing-based method, MeDIP-seq. Both methods were initially validated with respect to bisulfite sequencing as the gold standard and then assessed in terms of coverage, resolution and accuracy. The regions of the methylome that can be assayed by both methods and those that can only be assayed by one method were determined and the discovery of differentially methylated regions (DMRs) by both techniques was examined. Our results show that the Infinium HumanMethylation450 BeadChip® and MeDIP-seq show a good positive correlation (Spearman correlation of 0.68) on a genome-wide scale and can both be used successfully to determine differentially methylated loci in RefSeq genes, CpG islands, shores and shelves. MeDIP-seq however, allows a wider interrogation of methylated regions of the human genome, including thousands of non-RefSeq genes and repetitive elements, all of which may be of importance in disease. In our study MeDIP-seq allowed the detection of 15,709 differentially methylated regions, nearly twice as many as the array-based method (8070), which may result in a more comprehensive study of the methylome.

Analysing and interpreting DNA methylation data

DNA methylation is an epigenetic mark that has suspected regulatory roles in a broad range of biological processes and diseases. The technology is now available for studying DNA methylation genome-wide, at a high resolution and in a large number of samples. This Review discusses relevant concepts, computational methods and software tools for analysing and interpreting DNA methylation data. It focuses not only on the bioinformatic challenges of large epigenome-mapping projects and epigenome-wide association studies but also highlights software tools that make genome-wide DNA methylation mapping more accessible for laboratories with limited bioinformatics experience.

Evaluation of single CpG sites as proxies of CpG island methylation states at the genome scale

Methylation of a CpG island is a faithful marker of silencing of its associated gene. Different approaches report the methylation status of a CpG island based on the determination of one or a few CpG sites by assuming the homogeneity of methylation along the element. This strategy is frequently applied in both locus-specific and genome-wide studies, but often without a validation of the representativeness of the interrogated CpG site compared with the whole element. We have evaluated the predictive informativeness of the HpaII sites located in CpG islands using data from high-resolution methylome maps, which offer the possibility to assess the methylation homogeneity of each CpG island and to determine the reporter accuracy of single sites as surrogate markers. An excellent correlation was observed between the HpaII and CpG island methylation levels (r > 0.93). At the qualitative level, the predictive sensitivity of HpaII was >95% with >92% specificity for methylated CpG islands and >90% sensitivity with >95% specificity for unmethylated CpG islands. This analysis provides a global validation framework for strategies based on the use of the methylation-sensitive HpaII restriction enzyme.

DNA methylation based biomarkers: practical considerations and applications

A biomarker is a molecular target analyzed in a qualitative or quantitative manner to detect and diagnose the presence of a disease, to predict the outcome and the response to a specific treatment allowing personalized tailoring of patient management. Biomarkers can belong to different types of biochemical molecules such as proteins, DNA, RNA or lipids, whereby protein biomarkers have been the most extensively studied and used, notably in blood-based protein quantification tests or immunohistochemistry. The rise of interest in epigenetic mechanisms has allowed the identification of a new type of biomarker, DNA methylation, which is of great potential for many applications. This stable and heritable covalent modification mostly affects cytosines in the context of a CpG dinucleotide in humans. It can be detected and quantified by a number of technologies including genome-wide screening methods as well as locus- or gene-specific high-resolution analysis in different types of samples such as frozen tissues and FFPE samples, but also in body fluids such as urine, plasma, and serum obtained through non-invasive procedures. In some cases, DNA methylation based biomarkers have proven to be more specific and sensitive than commonly used protein biomarkers, which could clearly justify their use in clinics. However, very few of them are at the moment used in clinics and even less commercial tests are currently available. The objective of this review is to discuss the advantages of DNA methylation as a biomarker, the practical considerations for their development, and their use in disease detection, prediction of outcome or treatment response, through multiple examples mainly focusing on cancer, but also to evoke their potential for complex diseases and prenatal diagnostics.

Going beyond five bases in DNA sequencing

DNA sequencing has provided a wealth of information about biological systems, but thus far has focused on the four canonical bases, and 5-methylcytosine through comparison of the genomic DNA sequence to a transformed four-base sequence obtained after treatment with bisulfite. However, numerous other chemical modifications to the nucleotides are known to control fundamental life functions, influence virulence of pathogens, and are associated with many diseases. These modifications cannot be accessed with traditional sequencing methods. In this opinion, we highlight several emerging single-molecule sequencing techniques that have the potential to directly detect many types of DNA modifications as an integral part of the sequencing protocol.

Epigenome sequencing comes of age in development, differentiation and disease mechanism research

In eukaryotic organisms, changes in cell phenotype are tightly associated with dynamic changes in the epigenome. Over the past few years, sequencing-based genome-wide approaches to generate, analyze, interpret and integrate epigenetic information have been applied to investigate the mechanisms behind the changes in cell status, such as those which are seen in differentiation, disease and reprogramming. This article focuses on the four types of epigenomic information (i.e., nucleosome positioning, histone modification, DNA methylation and chromatin higher-order structure). We summarize the distinct high-throughput sequencing applications used to generate the different types of epigenomic profiles and the bioinformatic software available for performing routine analysis. With the dramatic improvement of sequencing technology and bioinformatic analysis, epigenome sequencing has gradually become the common approach to study a variety of biological issues.

DNA methyltransferase accessibility protocol for individual templates by deep sequencing

A single-molecule probe of chromatin structure can uncover dynamic chromatin states and rare epigenetic variants of biological importance that bulk measures of chromatin structure miss. In bisulfite genomic sequencing, each sequenced clone records the methylation status of multiple sites on an individual molecule of DNA. An exogenous DNA methyltransferase can thus be used to image nucleosomes and other protein-DNA complexes. In this chapter, we describe the adaptation of this technique, termed Methylation Accessibility Protocol for individual templates, to modern high-throughput sequencing, which both simplifies the workflow and extends its utility.

Epigenome-wide association studies for common human diseases

Despite the success of genome-wide association studies (GWASs) in identifying loci associated with common diseases, a substantial proportion of the causality remains unexplained. Recent advances in genomic technologies have placed us in a position to initiate large-scale studies of human disease-associated epigenetic variation, specifically variation in DNA methylation. Such epigenome-wide association studies (EWASs) present novel opportunities but also create new challenges that are not encountered in GWASs. We discuss EWAS design, cohort and sample selections, statistical significance and power, confounding factors and follow-up studies. We also discuss how integration of EWASs with GWASs can help to dissect complex GWAS haplotypes for functional analysis.

Methyl-Analyzer--whole genome DNA methylation profiling

SUMMARY

Methyl-Analyzer is a python package that analyzes genome-wide DNA methylation data produced by the Methyl-MAPS (methylation mapping analysis by paired-end sequencing) method. Methyl-MAPS is an enzymatic-based method that uses both methylation-sensitive and -dependent enzymes covering >80% of CpG dinucleotides within mammalian genomes. It combines enzymatic-based approaches with high-throughput next-generation sequencing technology to provide whole genome DNA methylation profiles. Methyl-Analyzer processes and integrates sequencing reads from methylated and unmethylated compartments and estimates CpG methylation probabilities at single base resolution.

AVAILABILITY AND IMPLEMENTATION

Methyl-Analyzer is available at http://github.com/epigenomics/methylmaps. Sample dataset is available for download at http://epigenomicspub.columbia.edu/methylanalyzer_data.html.

CONTACT

fgh3@columbia.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Epigenetic architecture and miRNA: reciprocal regulators

Deregulation of epigenetic and miRNA pathways are emerging as key events in carcinogenesis. miRNA genes can be epigenetically regulated and miRNAs can themselves repress key enzymes that drive epigenetic remodeling. Epigenetic and miRNA functions are thus tightly interconnected and crucial for maintaining correct local and global genomic architecture as well as gene-expression patterns, yet the underlying molecular mechanisms and their widespread effects remain poorly understood. Owing to the tissue specificity, versatility and relative stability of miRNAs, these small ncRNAs are considered especially promising in clinical applications, and their biogenesis and function is subject of active research. In this article, the current status of epigenetic miRNA regulation is summarized and future therapeutic prospects in the field are discussed with a focus on cancer.

Quantitative comparison of genome-wide DNA methylation mapping technologies

DNA methylation is a key component of mammalian gene regulation and the most classical example of an epigenetic mark. DNA methylation patterns are mitotically heritable and stable over time, but they undergo considerable changes in response to cell differentiation, diseases and environmental influences. Several methods have been developed for DNA methylation profiling on a genomic scale. Here, we benchmark four of these methods on two sample pairs, comparing their accuracy and power to detect DNA methylation differences. The results show that all evaluated methods (MeDIP-seq: methylated DNA immunoprecipitation, MethylCap-seq: methylated DNA capture by affinity purification, RRBS: reduced representation bisulfite sequencing, and the Infinium HumanMethylation27 assay) produce accurate DNA methylation data. However, these methods differ in their ability to detect differentially methylated regions between pairs of samples. We highlight strengths and weaknesses of the four methods and give practical recommendations for the design of epigenomic case-control studies.